Chapter 10.
Productivity Measures: Business Sector and Major
Subsectors

Data Sources and Estimating Procedures

Output per hour measures
Output. Real gross domestic product in the business
and nonfarm business sectors is the basis of the output
components of the major sector labor productivity and
multifactor productivity measures. These output
components are based on and are consistent with the
National Income and Product Accounts (NIPA), including
the gross domestic product (GDP) measure, prepared by the
Bureau of Economic Analysis (BEA) of the U.S. Department
of Commerce6.

Real business sector output is an annual-weighted
(Fisher-Ideal) index. It is constructed from the gross
domestic product (GDP) excluding the following outputs:
General government, nonprofit institutions, paid
employees of private households, and the rental value of
owner-occupied dwellings. These same exclusions are made
when calculating current dollar output for the sector.
The business sector thereby excludes many activities
where it is difficult to draw inferences on productivity
from NIPA output measures. Such inferences would be
questionable mainly because the output measures are based
largely on incomes of input factors. The farm sector,
which is subject to unique external forces, also is
excluded to yield the nonfarm business sector, the
principal focus of many productivity studies.
Nonfinancial corporate output is similar to that of the
business sector but also excludes unincorporated
businesses and those corporations which are depository
institutions, nondepository institutions, security and
commodity brokers, insurance carriers, regulated
investment offices, small business offices, and real
estate investment trusts.

Annual manufacturing indexes for both the quarterly
labor productivity and KLEMS multifactor productivity
measures are constructed by deflating the current-dollar
industry value of production provided by the U.S. Bureau
of the Census with data from BEA. These deflators are
constructed by BEA by combining data from the BLS
producer price program and other sources. The industry
shipments are aggregated using annual weights, and
intrasector transactions are removed7. Quarterly manufacturing output
measures are based on the index of industrial production
prepared monthly by the Board of Governors of the Federal
Reserve System, adjusted to be consistent with the annual
indexes of manufacturing sector output prepared by BLS.

Labor input. The primary source of hours and
employment data is the BLS Current Employment Statistics
(CES) program, which provides monthly survey data on
total employment and employment and average weekly hours
of production and nonsupervisory workers in
nonagricultural establishments. Jobs rather than persons
are counted, so that multiple jobholders are counted more
than once.

The CES data are based on payroll records from a
sample of establishments in which the probability of
sample selection is related to the establishment size.
Data on employment, hours, and earnings are collected
monthly; the reference period for these data is the
payroll period including the 12th of the month. (The CES
methods are described in chapter 2.) Establishment data
are published monthly in Employment and Earnings.

Because CES data include only nonfarm wage and salary
workers, data from the Current Population Survey (CPS)
are used for farm employment. In the nonfarm sector, the
CPS is also used for proprietors and unpaid family
workers. Government enterprise hours are developed from
the National Income and Product Accounts estimates of
employment and CPS data on average weekly hours.

Separate estimates for employment and hours paid are
developed for each major sector, converted to an
hours-at-work basis. The labor input of employees of
nonprofit corporations are estimated based on data from
the Commerce Department's Bureau of the Census and Bureau
of Economic Analysis and subtracted from the totals for
each major sector. Hours of labor input are treated as
homogeneous units; no distinction is made among workers
with different skill levels or wages.

For nonmanufacturing sectors, employment and average
weekly hours are computed from the CES, CPS, and NIPA
sources. Although CES data on average weekly hours refer
only to nonsupervisory workers, it is assumed for the
computation of hours that the length of the workweek in
each nonmanufacturing industry is the same for all wage
and salary workers.

In manufacturing, separate measures for production and
nonproduction workers' hours are derived and aggregated
to the manufacturing total. Employment and average weekly
hours for production workers and employment for
nonproduction workers are taken directly from CES data.
Average weekly hours for nonproduction workers were
developed from BLS studies of wages and supplements in
manufacturing which provide data on the regularly
scheduled workweek of white-collar employees.

In the CES, weekly hours are measured as hours paid
rather than hours at work. The Hours at Work Survey is
used to convert the hours paid of nonagricultural
production and nonsupervisory employees to an
hours-at-work basis.8
Hours at work exclude all forms of paid leave, but
include paid time to travel between job sites, coffee
breaks, and machine downtime. This survey of about 5,500
establishments has collected quarterly and annual ratios
of hours at work to hours paid since 1981.9 (See BLS form 2000P1 in the
printed edition of the Handbookof Methods for
a sample data collection form for manufacturing
industries. Form 2000N1 is a virtually identical form for
nonmanufacturing industries and is not reproduced.)
Ratios are developed for each 2-digit SIC industry within
manufacturing and for each 1-digit SIC industry outside
of manufacturing.

Unpublished data and one-time surveys have been used
to extend the annual ratios back to 1947 as well as
develop ratios for nonproduction and supervisory workers.10 The quarterly
ratios are not currently used in the quarterly measures
of labor input. Instead, a quadratic minimization formula
devised by Frank Denton is used to generate quarterly
ratios.11

The resultant quarterly measures are used to convert
the paid hours of nonfarm employees to an hours-at-work
basis. The estimates of hours of farm workers,
proprietors, unpaid family workers, employees of
government enterprises, and paid employees of private
households are collected on an hours-at-work basis. These
hours are only adjusted to include information on those
persons who are employed but not at work during the
survey week.

Compensation and labor costs. BEA develops
employee compensation data as part of the national income
accounts. These quarterly data include direct payments to
labor — wages and salaries (including executive
compensation), commissions, tips, bonuses, and payments
in kind representing income to the recipients — and
supplements to these direct payments. Supplements consist
of vacation and holiday pay, all other types of paid
leave, employer contributions to funds for social
insurance, private pension and health and welfare plans,
compensation for injuries, etc.

The compensation measures taken from establishment
payrolls refer exclusively to wage and salary workers.
Labor cost would be seriously understated by this measure
of employee compensation alone in sectors such as farm
and retail trade, where hours at work by proprietors
represent a substantial portion of total labor input.
BLS, therefore, imputes a compensation cost for labor
services of proprietors and includes the hours of unpaid
family workers in the hours of all employees engaged in a
sector. Labor compensation per hour for proprietors is
assumed to be the same as that of the average employee in
that sector for measures found in the BLS news release,
"Productivity
and Costs."

Multifactor productivity measures
Major sectors. The multifactor productivity indexes
for major sectors measure output per combined unit of
labor and capital input in private business and private
nonfarm business. The output measures for private
business and private nonfarm business are similar to the
Fisher-Ideal indexes of output for business and nonfarm
business except that output of government enterprises is
omitted. Estimates of the appropriate weights for labor
and capital in government enterprises cannot be made
because subsidies account for a substantial portion of
capital income.

Labor input for the multifactor productivity measures
in these sectors begins with hours at work data similar
to the hours in the quarterly labor productivity program
with two principle differences. First, the hours of
employees of government enterprises are excluded. Second,
the hours at work for each of 1,008 types of workers
classified by their educational attainment, work
experience and gender are aggregated using an annually
chained (Tornqvist) index. The growth rate of the
aggregate is therefore a weighted average of the growth
rates of each type of worker where the weight assigned to
a type of worker is its share of total labor
compensation. The resulting aggregate measure of labor
input accounts for both the increase in raw hours at work
and changes in the skill composition (as measured by
education and work experience) of the work force.12

Capital inputs for the multifactor productivity
measures are computed in accordance with a service flow
concept for physical capital assets — equipment,
structures, inventories, and land. Capital inputs for
major sectors are determined in three main steps: 1) A
very detailed array of capital stocks is developed for
various asset types in various industries; 2) asset-type
capital stocks are aggregated for each industry to
measure capital input for the industry; and 3) industry
capital inputs are aggregated to measure sectoral level
capital input.

The asset detail consists of 28 types of equipment, 22
types of nonresidential structures, 9 types of
residential structures (owner-occupied housing is
excluded), 3 types of inventories (by stage of
processing), and land. BLS measures of capital stocks for
equipment and structures are prepared using NIPA data on
real gross investment. Real stocks are constructed as
vintage aggregates of historical investments (in real
terms) in accordance with an "efficiency" or
service flow concept (as distinct from a price or value
concept). The efficiency of each asset is assumed to
deteriorate only gradually during the early years of an
asset's service life and then more quickly later in its
life. These "age/efficiency" schedules are
based, to the extent possible, on empirical evidence of
capital deterioration. Inventory stocks are developed
using data from the NIPA. Farm land input is based on
data from the Economic Research Service of the U.S.
Department of Agriculture. A benchmark for nonfarm land
is estimated by applying a land-structure ratio based on
unpublished estimates by the Bureau of the Census to BLS
estimates of the value of structures. This benchmark is
extrapolated using gross stocks of structures calculated
from Bureau of Economic Analysis investment data. The
resulting nonfarm land data series is allocated to
industries based on Internal Revenue Service data on book
values of land.13

For each industry (the BLS procedures are applied to
57 industries in the private business sector
corresponding, approximately, to the 2-digit SIC level),
these measures of capital stocks are aggregated using a
Tornqvist chain index procedure (described below). The
weight for each asset type is based on the share of
property income estimated to be accruing to that asset
type in each industry averaged over 2 years. Property
income in each industry is allocated to asset types by
employing estimates of the "implicit rental
prices" of each asset type.14
The implicit rental price concept is based on the
neoclassical theory of the firm and provides a framework
for deriving weights for asset-type capital stocks.
Because some asset types tend to deteriorate much more
quickly than others and because of tax rules specific to
asset types, the real economic cost of employing a
dollar's worth of stock varies substantially by asset
type.

At the sector level, aggregate capital input is
obtained by further chained (Tornqvist) aggregation of
each industry's capital input using each industry's
two-period average share of total capital income as
weights.

Once the sector's capital input is measured, total
input is computed by aggregating capital and labor. For
each input, the weight is the input's share of total
costs and is derived from NIPA data on the components of
nominal gross product originating (GPO) by industry. At
both the sector and the industry levels, labor costs are
measured as compensation to employees (wages, salaries,
and supplements) plus a portion of noncorporate income.15 Most other
components of nominal GPO are assigned to capital.16 The exception is
those indirect taxes which are not assigned either to
capital or labor (notably sales and excise taxes). Thus
total cost is less than GPO by an amount equal to these
taxes. Labor and capital shares in total cost are
computed and then used in the aforementioned aggregation
of capital and labor.17
Finally, major sector multifactor productivity indexes
are calculated as the ratio of output to input.

Manufacturing industries. Multifactor
productivity indexes for aggregate manufacturing and for
20 manufacturing industries also measure output per unit
of input. In this case, input is a weighted aggregate of
capital, labor, energy, nonenergy materials, and
purchased business services inputs.18

For these multifactor productivity manufacturing
measures, output is the deflated value of production,
adjusted for inventory change, shipped to purchasers
outside of the industry and not just final users. Hence,
it differs from the output measures used for the major
sector multifactor productivity indexes. Capital is
measured as it is for the major sector multifactor
productivity indexes; rental prices of capital are
computed for each industry. However, labor is measured as
a direct summation of hours at work rather than as the
Tornqvist index method used in the major sector
multifactor productivity measures.

The inclusion in the industry multifactor productivity
measures of all intermediate inputs — energy,
nonenergy materials, and purchased business
services — is consistent with the use of total value
of production as the output measure. Energy input is
constructed using data on the price and quantity of fuels
purchased for use as heat or power. Nonenergy materials
input includes all commodity inputs exclusive of fuels
but inclusive of fuel-type inputs used as raw materials
in manufacturing. The measures of purchased business
services are constructed using price and value data on
services purchased by manufacturing industries from
service industries. Data sources used in constructing
these three inputs include input-output tables, surveys
of establishments in manufacturing and other industries,
and price indexes.

Total input is computed from components as a Tornqvist
chain index number series. The weight for each input is
its share in total input cost. The multifactor
productivity industry measures are available for 1949 to
the present.

Footnotes6 A detailed description of the methods and
procedures for estimating GNP and GDP in current and
constant dollars is given in Carol S. Carson, "GNP:
An Overview of Sources Data and Estimating Methods,"
Survey of Current Business, July 1987, pp. 103-26.
Also see Methodology Paper No. 1 "Introduction to
National Income Accounting" (Bureau of Economic
Analysis, 1985). The current chain-type annual-weighted
quantity measures are discussed in Allan H. Young,
"Alternative Measures of Change in Real Output and
Prices," Survey of Current Business, April
1992, pp. 32-48. These official introduction of these
measures into the National Accounts is discussed in J.
Steven Landefeld and Robert P. Parker, "Preview of
the Comprehensive Revision of the National Income and
Product Accounts: BEA's New Featured Measures of Output
and Prices," Survey of Current Business,
July, 1995, pp. 31-38. Derivation of business sector
output is discussed also in Jerome A. Mark,
"Measuring Single-Factor and Multifactor
Productivity, Monthly Labor Review, December 1986,
pp. 3-11.7 A discussion of manufacturing output measures
is given in William Gullickson, "Measurement of
productivity growth in U.S. manufacturing," Monthly
Labor Review, July 1995, pp. 13-28. 8 Kent Kunze, "A New BLS Survey Measures the
Ratio of Hours Worked to Hours Paid," Monthly
Labor Review, June 1984, pp. 3-7. 9 The sample design and universe of
establishments for the Hours at Work survey are
essentially the same as those used in the Current
Establishments Statistics program. The response rate has
ranged from 70 to more than 80 percent including
responses obtained through computer assisted telephone
interviews. 10 A description of the hours at work ratios for
the period 1948 through 1988 can be found in Mary
Jablonski, Kent Kunze, and Phyllis Flohr Otto,
"Hours at Work: A New Base for Productivity
Statistics," Monthly Labor Review, February
1990, pp. 17-24. 11 See Frank T. Denton, "Adjustment of
Monthly and Quarterly Series to Annual Totals: An
Approach Based on Quadratic Minimization," Journal
of the American Statistical Association, March 1971,
pp. 99-102. This method is also used to produce quarterly
ratios prior to 1981.12 See Labor Composition and US Productivity
Growth, 1948-90 for a complete description of
Tornqvist aggregation of hours. 13 These methods are described in detail in Trends
in Multifactor Productivity, 1948-81, appendix C. 14 The rental price formula and related
methodology and data sources are described in Trends
in Multifactor Productivity, 1948-81, appendix C. The
rental price formulas described in this publication have
been modified to eliminate large fluctuations due to
inflation in new goods prices. Research on this issue is
reported by Michael J. Harper, Ernst R. Berndt and David
O. Wood, "Rates of Return and Capital Aggregation
Using Alternative Rental Prices," in Dale W.
Jorgenson and Ralph Landau, Technology and Capital
Formation, 1989, MIT Press, pp. 331-37.15 Noncorporate income is allocated to labor and
capital costs in each year using the following
assumption: Initially self-employed persons are assumed
to receive the same hourly compensation as employees and
the rate of return to non-corporate capital is assumed to
be the same as in the corporate sector. Based on these
assumptions, the resultant income of proprietors is
adjusted to match proprietors income reported in the GPO
data by scaling proportionately the hourly compensation
of the self-employed and the noncorporate rate of return.
This treats any apparent excess or deficiency in
noncorporate income neutrally with respect to labor and
capital. 16 Capital costs are the sum of 1) the balance of
noncorporate income, 2) corporate profits, 3) net
interest, 4) rental income, 5) adjusted capital
consumption allowance, 6) inventory valuation
adjustments, and 7) portions of indirect taxes assumed to
be associated with capital (notably motor vehicle and
property taxes), 8) the sum of business transfers and
government subsidies. 17 Excluding these indirect business taxes from
the calculation of factor shares has the effect of
assuming the incidence of these taxes are neutral with
respect to capital and labor income. 18 An explanation of the methods and some results
are presented in William Gullickson and Michael J.
Harper, "Multifactor Productivity in U.S.
Manufacturing, 1949-83," Monthly Labor Review,
October 1987, pp. 18-28.